Recent developments in in-memory technology have implemented in-memory databases in analytic data processing systems in place of the traditional database management systems (DBMS). An example of an in-memory data processing system is the In-memory Appliance (HANA™) from SAP AG. An in-memory data processing system may perform both transactional and analytic data processing due to the speed available from storing the data in main memory (as opposed to the disk storage of non-in-memory database systems).
In-memory data processing systems enable organizations to analyze their business operations using huge volumes of detailed information while the business is running. In-memory computing technology allows the processing of massive quantities of data in main memory to provide immediate results from analysis and transaction. The data to be processed is ideally real-time data (that is, data that is available for processing or analysis immediately after it is created). This enables organizations to instantly explore and analyze all of its transactional and analytical data in real time.
In-memory data processing systems may consist of several parts including an in-memory database (e.g., SAP HANA database) and database administration and development tool (e.g., SAP HANA studio). In-memory databases may have column and row store capabilities which allows high-performance processing and analysis of data already on the database and therefore prevents the necessity to transfer data from the database to on application server. Further, the in-memory database allows for modeling data as tables and views. Tables are tabular data structures, each row identifying a particular entity, and each column having a unique name. Views are combinations and selections of data from tables modeled to serve a particular purpose.
The database administration and development tool, also referred to as database modeler is a graphical data modeling tool which allows you to design analytical models and analytical privileges that govern the access to those models. The information model designing process in the database modeler involves building data foundation for creating information models. The data foundation is a schema that defines the relevant tables and relationships from one or more relational databases.
On the other hand, semantic based information design tools (e.g., SAP Business Objects information Design Tool) involve a data abstraction layer called a semantic layer which is a collection of classes and objects (data foundation). Semantic layer based data foundation consists of subject area specific data foundation objects that are large with tables, relationships and cardinality. However, current users of semantic based information design tools who want to adopt in-memory computing technology, have to manually re-create the entire data foundation of tables and relationships by understanding the existing semantic layer data foundation.